Computer-implemented methods leverage internal data accumulated by a banking institution including merchant sales data and customer purchasing data, in order to best implement merchant offer campaigns by computing a set of "good campaigns" for a given user in real time, while maximizing the success of all active campaigns. (Fig. 1) Multiple factors (208, 210, 212, 214, 216) may be statistically evaluated and combined (218, 220) to determine the best campaigns for a given user. Other considerations preferably relate directly to a level of accomplishment of the active campaigns and their time remaining. Machine learning may be applied to assess a predicted level of interest of each user for the active campaigns (Fig. 3). In some embodiments, the respective weights of various factors can be changed in order to adapt the algorithm to specific business goals.
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